Hybrid sparse resultant matrices for bivariate systems

Our main contribution is an explicit construction of square resultant matrices, which are submatrices of those introduced by Cattani, Dickenstein and Sturmfels [4]. The determinant is a nontrivial multiple of the sparse (or toric) resultant. The matrix is hybrid in that it contains a submatrix of Sy...

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Autores principales: D'Andrea, C., Emiris, I.Z.
Formato: CONF
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Acceso en línea:http://hdl.handle.net/20.500.12110/paper_NIS02119_v_n_p24_DAndrea
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spelling todo:paper_NIS02119_v_n_p24_DAndrea2023-10-03T16:45:44Z Hybrid sparse resultant matrices for bivariate systems D'Andrea, C. Emiris, I.Z. Convexity Mixed subdivision Piecewise-linear lifting Sparse resultant matrix Toric Jacobian Algorithms Boundary conditions Combinatorial mathematics Computer aided design Computer simulation Eigenvalues and eigenfunctions Geometry Piecewise linear techniques Polynomials Vectors Bivariate systems Mixed subdivision Newton polygons Piecewise linear lifting Sparse resultant matrix Toric Jacobian Matrix algebra Our main contribution is an explicit construction of square resultant matrices, which are submatrices of those introduced by Cattani, Dickenstein and Sturmfels [4]. The determinant is a nontrivial multiple of the sparse (or toric) resultant. The matrix is hybrid in that it contains a submatrix of Sylvester type and an additional row expressing the toric Jacobian. If we restrict attention to such matrices, the algorithm yields the smallest possible matrix in general. This is achieved by strongly exploiting the combinatorics of sparse elimination. The algorithm uses a new piecewise-linear lifting, defined for bivariate systems of 3 polynomials with Newton polygons being scaled copies of a single polygon. The major motivation comes from systems encountered in CAD. Our Maple implementation, applied to certain examples, illustrates our construction and compares with alternative matrices. Fil:D'Andrea, C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_NIS02119_v_n_p24_DAndrea
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Convexity
Mixed subdivision
Piecewise-linear lifting
Sparse resultant matrix
Toric Jacobian
Algorithms
Boundary conditions
Combinatorial mathematics
Computer aided design
Computer simulation
Eigenvalues and eigenfunctions
Geometry
Piecewise linear techniques
Polynomials
Vectors
Bivariate systems
Mixed subdivision
Newton polygons
Piecewise linear lifting
Sparse resultant matrix
Toric Jacobian
Matrix algebra
spellingShingle Convexity
Mixed subdivision
Piecewise-linear lifting
Sparse resultant matrix
Toric Jacobian
Algorithms
Boundary conditions
Combinatorial mathematics
Computer aided design
Computer simulation
Eigenvalues and eigenfunctions
Geometry
Piecewise linear techniques
Polynomials
Vectors
Bivariate systems
Mixed subdivision
Newton polygons
Piecewise linear lifting
Sparse resultant matrix
Toric Jacobian
Matrix algebra
D'Andrea, C.
Emiris, I.Z.
Hybrid sparse resultant matrices for bivariate systems
topic_facet Convexity
Mixed subdivision
Piecewise-linear lifting
Sparse resultant matrix
Toric Jacobian
Algorithms
Boundary conditions
Combinatorial mathematics
Computer aided design
Computer simulation
Eigenvalues and eigenfunctions
Geometry
Piecewise linear techniques
Polynomials
Vectors
Bivariate systems
Mixed subdivision
Newton polygons
Piecewise linear lifting
Sparse resultant matrix
Toric Jacobian
Matrix algebra
description Our main contribution is an explicit construction of square resultant matrices, which are submatrices of those introduced by Cattani, Dickenstein and Sturmfels [4]. The determinant is a nontrivial multiple of the sparse (or toric) resultant. The matrix is hybrid in that it contains a submatrix of Sylvester type and an additional row expressing the toric Jacobian. If we restrict attention to such matrices, the algorithm yields the smallest possible matrix in general. This is achieved by strongly exploiting the combinatorics of sparse elimination. The algorithm uses a new piecewise-linear lifting, defined for bivariate systems of 3 polynomials with Newton polygons being scaled copies of a single polygon. The major motivation comes from systems encountered in CAD. Our Maple implementation, applied to certain examples, illustrates our construction and compares with alternative matrices.
format CONF
author D'Andrea, C.
Emiris, I.Z.
author_facet D'Andrea, C.
Emiris, I.Z.
author_sort D'Andrea, C.
title Hybrid sparse resultant matrices for bivariate systems
title_short Hybrid sparse resultant matrices for bivariate systems
title_full Hybrid sparse resultant matrices for bivariate systems
title_fullStr Hybrid sparse resultant matrices for bivariate systems
title_full_unstemmed Hybrid sparse resultant matrices for bivariate systems
title_sort hybrid sparse resultant matrices for bivariate systems
url http://hdl.handle.net/20.500.12110/paper_NIS02119_v_n_p24_DAndrea
work_keys_str_mv AT dandreac hybridsparseresultantmatricesforbivariatesystems
AT emirisiz hybridsparseresultantmatricesforbivariatesystems
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